高炉炼铁中高铝渣实践的优化:工业方法。第2部分:数据驱动方面

IF 1.7 3区 材料科学 Q2 METALLURGY & METALLURGICAL ENGINEERING
S. Pal, Manisha Sahoo, Devi Dutta Biswajeet, Sujan Hazra, Garwa Sunny Tarachand, Debanjana Bhattacharyya, S. Nag, S. Seetharaman
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引用次数: 0

摘要

高炉炉渣的输运和热力学性质的预测在实验上是一项繁琐的工作。文献研究表明,使用机器学习来确定性质作为组成的函数是一种有效的玻璃渣技术。然而,机器学习和数据科学技术在高铝渣性能预测中的应用至今尚未得到广泛的研究。在本文中,使用支持向量机(SVM)和ExtraTrees回归器来预测高氧化铝体系(即Al2O3从18到22 wt-%变化)的高炉型炉渣的粘度、液相温度和其他热力学性质。通过改变MgO含量和CaO/SiO2比,分别在8 ~ 12 wt %和0.8 ~ 1.2 wt %范围内,研究了将高铝渣的有害影响最小化的方法。模型的精度已调整到相当高,并对预测结果进行了讨论,并讨论了在高炉炉渣高铝状态下运行的可能解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of high alumina slag practice in blast furnace ironmaking: an industrial approach. Part 2: Data-driven aspects
ABSTRACT The prediction of transport and thermodynamic properties of the blast furnace slag is an experimentally tedious job to accomplish as seen in part-1 of this work. Literature studies have shown that the use of machine learning in the determination of the properties as a function of composition is an effective technique for glassy slags. However, the application of machine learning and data science techniques in the prediction of high alumina slag properties has not been studied extensively so far. In this paper, the use of Support Vector Machine (SVM) and ExtraTrees Regressor have been done to predict the viscosity, liquidus temperature, and other thermodynamic properties of blast furnace type slag in the high alumina regime, i.e. Al2O3 varying from 18 to 22 wt-%. The minimization of detrimental effects of high alumina slag has been studied by varying the MgO content and CaO/SiO2 ratio in the range of 8–12 wt-% and 0.8–1.2, respectively. The accuracy of models has been tuned to be fairly high and the results of the prediction have been discussed with possible solutions to operate under the high alumina regime of blast furnace slag.
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来源期刊
Ironmaking & Steelmaking
Ironmaking & Steelmaking 工程技术-冶金工程
CiteScore
3.70
自引率
9.50%
发文量
125
审稿时长
2.9 months
期刊介绍: Ironmaking & Steelmaking: Processes, Products and Applications monitors international technological advances in the industry with a strong element of engineering and product related material. First class refereed papers from the international iron and steel community cover all stages of the process, from ironmaking and its attendant technologies, through casting and steelmaking, to rolling, forming and delivery of the product, including monitoring, quality assurance and environmental issues. The journal also carries research profiles, features on technological and industry developments and expert reviews on major conferences.
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